Multi-criteria group decision analytics for sustainable supplier relationship management in a focal manufacturing company

In the context of sustainable development, while the benefits of incorporating environmental, social, and governance (ESG) considerations into supplier management have been widely discussed in recent years, a significant gap in the literature remains. Specifically, there is a lack of a standardized decision analytics framework for ESG-oriented supplier relationship management (SRM) processes in the manufacturing sector. To address this gap, this study introduces a multi-criteria supplier analytics framework (MCSAF) towards sustainable SRM. Through referring traditional supplier evaluation criteria as well as emerging ESG criteria, a novel decision hierarchy for supplier segmentation is developed. The proposed system utilizes the Bayesian best-worst method and the Canopy-k-means clustering algorithm to formulate different supplier segments for strategic development. The proposed MCSAF has been successfully implemented in a German solar water pump manufacturer. The results show that the five highest-ranked criteria are 'Quality', 'Impact and importance on product quality and business growth', 'Environmental policy/management', 'Customer and product responsibility', and 'Risk and crisis management'. 52 suppliers are categorized into five segments, leading to the formulation of ESG-enabled supplier development strategies are subsequently formulated. The successful implementation of the MCSAF showcases its effectiveness in advancing ESG practices in sustainable supplier management.